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python-development-python-scaffoldPython 开发 Python scaffold

Agent Skill

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

总安装

737

周安装

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:python-development-python-scaffold(Python 开发 Python scaffold)
来源仓库:https://github.com/rmyndharis/antigravity-skills
仓库路径:skills/python-development-python-scaffold
安装命令:
npx skills add https://github.com/rmyndharis/antigravity-skills --skill python-development-python-scaffold
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/rmyndharis/antigravity-skills --skill python-development-python-scaffold

简介

用于快速生成标准化的 Python 项目脚手架。

  • 适合初始化新项目结构、配置文件模板生成。
  • 包含测试目录、CI/CD 配置等常见工程组件。
  • 可根据需求定制目录层级和初始文件内容。python-development-python-scaffold 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 生成后建议人工复核敏感配置项如密钥路径。

SKILL.md

Python Project Scaffolding

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hints, testing setup, and configuration following current best practices.

Use this skill when

  • Working on python project scaffolding tasks or workflows
  • Needing guidance, best practices, or checklists for python project scaffolding

Do not use this skill when

  • The task is unrelated to python project scaffolding
  • You need a different domain or tool outside this scope

Context

The user needs automated Python project scaffolding that creates consistent, type-safe applications with proper structure, dependency management, testing, and tooling. Focus on modern Python patterns and scalable architecture.

Requirements

$ARGUMENTS

Instructions

1. Analyze Project Type

Determine the project type from user requirements:

  • FastAPI: REST APIs, microservices, async applications
  • Django: Full-stack web applications, admin panels, ORM-heavy projects
  • Library: Reusable packages, utilities, tools
  • CLI: Command-line tools, automation scripts
  • Generic: Standard Python applications

2. Initialize Project with uv

# Create new project with uv
uv init <project-name>
cd <project-name>

# Initialize git repository
git init
echo ".venv/" >> .gitignore
echo "*.pyc" >> .gitignore
echo "__pycache__/" >> .gitignore
echo ".pytest_cache/" >> .gitignore
echo ".ruff_cache/" >> .gitignore

# Create virtual environment
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Generate FastAPI Project Structure

fastapi-project/
├── pyproject.toml
├── README.md
├── .gitignore
├── .env.example
├── src/
│   └── project_name/
│       ├── __init__.py
│       ├── main.py
│       ├── config.py
│       ├── api/
│       │   ├── __init__.py
│       │   ├── deps.py
│       │   ├── v1/
│       │   │   ├── __init__.py
│       │   │   ├── endpoints/
│       │   │   │   ├── __init__.py
│       │   │   │   ├── users.py
│       │   │   │   └── health.py
│       │   │   └── router.py
│       ├── core/
│       │   ├── __init__.py
│       │   ├── security.py
│       │   └── database.py
│       ├── models/
│       │   ├── __init__.py
│       │   └── user.py
│       ├── schemas/
│       │   ├── __init__.py
│       │   └── user.py
│       └── services/
│           ├── __init__.py
│           └── user_service.py
└── tests/
    ├── __init__.py
    ├── conftest.py
    └── api/
        ├── __init__.py
        └── test_users.py

pyproject.toml:

[project]
name = "project-name"
version = "0.1.0"
description = "FastAPI project description"
requires-python = ">=3.11"
dependencies = [
    "fastapi>=0.110.0",
    "uvicorn[standard]>=0.27.0",
    "pydantic>=2.6.0",
    "pydantic-settings>=2.1.0",
    "sqlalchemy>=2.0.0",
    "alembic>=1.13.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=8.0.0",
    "pytest-asyncio>=0.23.0",
    "httpx>=0.26.0",
    "ruff>=0.2.0",
]

[tool.ruff]
line-length = 100
target-version = "py311"

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]

[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"

src/project_name/main.py:

from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

from .api.v1.router import api_router
from .config import settings

app = FastAPI(
    title=settings.PROJECT_NAME,
    version=settings.VERSION,
    openapi_url=f"{settings.API_V1_PREFIX}/openapi.json",
)

app.add_middleware(
    CORSMiddleware,
    allow_origins=settings.ALLOWED_ORIGINS,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

app.include_router(api_router, prefix=settings.API_V1_PREFIX)

@app.get("/health")
async def health_check() -> dict[str, str]:
    return {"status": "healthy"}

4. Generate Django Project Structure

# Install Django with uv
uv add django django-environ django-debug-toolbar

# Create Django project
django-admin startproject config .
python manage.py startapp core

pyproject.toml for Django:

[project]
name = "django-project"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = [
    "django>=5.0.0",
    "django-environ>=0.11.0",
    "psycopg[binary]>=3.1.0",
    "gunicorn>=21.2.0",
]

[project.optional-dependencies]
dev = [
    "django-debug-toolbar>=4.3.0",
    "pytest-django>=4.8.0",
    "ruff>=0.2.0",
]

5. Generate Python Library Structure

library-name/
├── pyproject.toml
├── README.md
├── LICENSE
├── src/
│   └── library_name/
│       ├── __init__.py
│       ├── py.typed
│       └── core.py
└── tests/
    ├── __init__.py
    └── test_core.py

pyproject.toml for Library:

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "library-name"
version = "0.1.0"
description = "Library description"
readme = "README.md"
requires-python = ">=3.11"
license = {text = "MIT"}
authors = [
    {name = "Your Name", email = "email@example.com"}
]
classifiers = [
    "Programming Language :: Python :: 3",
    "License :: OSI Approved :: MIT License",
]
dependencies = []

[project.optional-dependencies]
dev = ["pytest>=8.0.0", "ruff>=0.2.0", "mypy>=1.8.0"]

[tool.hatch.build.targets.wheel]
packages = ["src/library_name"]

6. Generate CLI Tool Structure

# pyproject.toml
[project.scripts]
cli-name = "project_name.cli:main"

[project]
dependencies = [
    "typer>=0.9.0",
    "rich>=13.7.0",
]

src/project_name/cli.py:

import typer
from rich.console import Console

app = typer.Typer()
console = Console()

@app.command()
def hello(name: str = typer.Option(..., "--name", "-n", help="Your name")):
    """Greet someone"""
    console.print(f"[bold green]Hello {name}![/bold green]")

def main():
    app()

7. Configure Development Tools

.env.example:

# Application
PROJECT_NAME="Project Name"
VERSION="0.1.0"
DEBUG=True

# API
API_V1_PREFIX="/api/v1"
ALLOWED_ORIGINS=["http://localhost:3000"]

# Database
DATABASE_URL="postgresql://user:pass@localhost:5432/dbname"

# Security
SECRET_KEY="your-secret-key-here"

Makefile:

.PHONY: install dev test lint format clean

install:
	uv sync

dev:
	uv run uvicorn src.project_name.main:app --reload

test:
	uv run pytest -v

lint:
	uv run ruff check .

format:
	uv run ruff format .

clean:
	find . -type d -name __pycache__ -exec rm -rf {} +
	find . -type f -name "*.pyc" -delete
	rm -rf .pytest_cache .ruff_cache

Output Format

  1. Project Structure: Complete directory tree with all necessary files
  2. Configuration: pyproject.toml with dependencies and tool settings
  3. Entry Point: Main application file (main.py, cli.py, etc.)
  4. Tests: Test structure with pytest configuration
  5. Documentation: README with setup and usage instructions
  6. Development Tools: Makefile,.env.example,.gitignore

Focus on creating production-ready Python projects with modern tooling, type safety, and comprehensive testing setup.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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按下载量换算78

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22.66%
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按下载量换算39

Gemini CLI

11.59%
按下载量换算30

Antigravity

7.43%
按下载量换算19

windsurf

3.01%
按下载量换算8

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执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/rmyndharis/antigravity-skills --skill python-development-python-scaffold;npx skills add rmyndharis/antigravity-skills --skill "python-development-python-scaffold" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

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